
TL;DR
This paper investigates how a society's ability to correctly aggregate information depends on the influence of highly connected, uninformed leaders and the initial noise in individual knowledge, revealing phase transitions in decision accuracy.
Contribution
It introduces a stylized model analyzing the impact of uninformed leaders on information aggregation and identifies phase transitions based on noise levels and leader clique size.
Findings
Identifies a transition from correct to incorrect aggregation as noise increases.
Shows the influence of leader clique size on the accuracy of collective decisions.
Reveals a singular behavior when the leader clique size approaches zero.
Abstract
The ability of a society to make the right decisions on relevant matters relies on its capability to properly aggregate the noisy information spread across the individuals it is made of. In this paper we study the information aggregation performance of a stylized model of a society whose most influential individuals - the leaders - are highly connected among themselves and uninformed. Agents update their state of knowledge in a Bayesian manner by listening to their neighbors. We find analytical and numerical evidence of a transition, as a function of the noise level in the information initially available to agents, from a regime where information is correctly aggregated to one where the population reaches consensus on the wrong outcome with finite probability. Furthermore, information aggregation depends in a non-trivial manner on the relative size of the clique of leaders, with the…
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